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start depcrecation cycle for lora_attention_proc 👋 (#7007)

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Sayak Paul
2024-02-18 13:11:30 +05:30
committed by GitHub
parent 3a7e481611
commit d4ade821cd
1 changed files with 6 additions and 34 deletions
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src/diffusers/models/attention_processor.py
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@@ -1809,24 +1809,7 @@ class SpatialNorm(nn.Module):
return new_f
## Deprecated
class LoRAAttnProcessor(nn.Module):
r"""
Processor for implementing the LoRA attention mechanism.
Args:
hidden_size (`int`, *optional*):
The hidden size of the attention layer.
cross_attention_dim (`int`, *optional*):
The number of channels in the `encoder_hidden_states`.
rank (`int`, defaults to 4):
The dimension of the LoRA update matrices.
network_alpha (`int`, *optional*):
Equivalent to `alpha` but it's usage is specific to Kohya (A1111) style LoRAs.
kwargs (`dict`):
Additional keyword arguments to pass to the `LoRALinearLayer` layers.
"""
def __init__(
self,
hidden_size: int,
@@ -1835,6 +1818,9 @@ class LoRAAttnProcessor(nn.Module):
network_alpha: Optional[int] = None,
**kwargs,
):
deprecation_message = "Using LoRAAttnProcessor is deprecated. Please use the PEFT backend for all things LoRA. You can install PEFT by running `pip install peft`."
deprecate("LoRAAttnProcessor", "0.30.0", deprecation_message, standard_warn=False)
super().__init__()
self.hidden_size = hidden_size
@@ -1883,23 +1869,6 @@ class LoRAAttnProcessor(nn.Module):
class LoRAAttnProcessor2_0(nn.Module):
r"""
Processor for implementing the LoRA attention mechanism using PyTorch 2.0's memory-efficient scaled dot-product
attention.
Args:
hidden_size (`int`):
The hidden size of the attention layer.
cross_attention_dim (`int`, *optional*):
The number of channels in the `encoder_hidden_states`.
rank (`int`, defaults to 4):
The dimension of the LoRA update matrices.
network_alpha (`int`, *optional*):
Equivalent to `alpha` but it's usage is specific to Kohya (A1111) style LoRAs.
kwargs (`dict`):
Additional keyword arguments to pass to the `LoRALinearLayer` layers.
"""
def __init__(
self,
hidden_size: int,
@@ -1908,6 +1877,9 @@ class LoRAAttnProcessor2_0(nn.Module):
network_alpha: Optional[int] = None,
**kwargs,
):
deprecation_message = "Using LoRAAttnProcessor is deprecated. Please use the PEFT backend for all things LoRA. You can install PEFT by running `pip install peft`."
deprecate("LoRAAttnProcessor2_0", "0.30.0", deprecation_message, standard_warn=False)
super().__init__()
if not hasattr(F, "scaled_dot_product_attention"):
raise ImportError("AttnProcessor2_0 requires PyTorch 2.0, to use it, please upgrade PyTorch to 2.0.")